haoliuhl / hybrid-discriminative-generative
Hybrid Discriminative-Generative Training via Contrastive Learning
☆75Updated last year
Alternatives and similar repositories for hybrid-discriminative-generative:
Users that are interested in hybrid-discriminative-generative are comparing it to the libraries listed below
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆68Updated 4 years ago
- Implicit Generation and Generalization in Energy Based Models in PyTorch☆65Updated 5 years ago
- Variational Autoencoder with Spatial Broadcast Decoder☆35Updated 5 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- [ICLR 2020] FSPool: Learning Set Representations with Featurewise Sort Pooling☆42Updated last year
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- ☆34Updated 3 years ago
- ☆34Updated 3 years ago
- Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020☆36Updated last year
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆39Updated 4 years ago
- Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)☆83Updated 2 years ago
- Memory efficient MAML using gradient checkpointing☆83Updated 5 years ago
- Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).☆22Updated 2 years ago
- The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…☆40Updated 4 years ago
- ☆75Updated 8 months ago
- Implementation of the paper "Direct Optimization through argmax for discrete Variational Auto-Encoder"☆14Updated 4 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 2 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- ☆26Updated 6 years ago
- Estimating Gradients for Discrete Random Variables by Sampling without Replacement☆39Updated 4 years ago
- ☆49Updated 3 years ago
- Experiments for Meta-Learning Symmetries by Reparameterization☆56Updated 3 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- GAN(TK)²: GAN Neural Tangent Kernel ToolKit☆13Updated 2 years ago
- ☆63Updated 11 months ago
- Masked Convolutional Flow☆59Updated 4 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 4 years ago
- Reparameterize your PyTorch modules☆70Updated 4 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago